The role of antibiotic exposure and the effects of breastmilk and human milk feeding on the developing infant gut microbiome

The World Health Organization (WHO) recommends exclusive breastfeeding for the first 6 months of life followed by complementary foods and sustained breastfeeding for at least 2 years, underscoring its pivotal role in reducing infant mortality and preventing various illnesses. This perspective delves into the intricate relationship between breastfeeding practices, early life antibiotic exposure, and infant gut microbiome development, highlighting their profound influence on child health outcomes. Antibiotics are extensively prescribed during pregnancy and childhood, disrupting the microbiome, and are related to increased risks of allergies, obesity, and neurodevelopmental disorders. Breastfeeding is a significant determinant of a healthier gut microbiome, characterized by higher levels of beneficial bacteria such as Bifidobacterium and lower levels of potential pathogens. Despite widespread recognition of the benefits of breastfeeding, gaps persist in healthcare practices and support mechanisms, exacerbating challenges faced by breastfeeding families. This highlights the pressing need for comprehensive research encompassing breastfeeding behaviors, human milk intake, and their impact on infant health outcomes. Additionally, promoting awareness among healthcare providers and families regarding the detrimental effects of unnecessary formula supplementation could facilitate informed decision-making and bolster exclusive breastfeeding rates. Moreover, donor human milk (DHM) is a promising alternative to formula, potentially mitigating disruptions to the infant gut microbiome after antibiotic exposure. Overall, prioritizing breastfeeding support interventions and bridging research gaps are essential steps towards improving child health outcomes on a global scale

The international perinatal outcomes in the pandemic (iPOP) study: Protocol

Preterm birth is the leading cause of infant death worldwide, but the causes of preterm birth are largely unknown. During the early COVID-19 lockdowns, dramatic reductions in preterm birth were reported; however, these trends may be offset by increases in stillbirth rates. It is important to study these trends globally as the pandemic continues, and to understand the underlying cause(s). Lockdowns have dramatically impacted maternal workload, access to healthcare, hygiene practices, and air pollution - all of which could impact perinatal outcomes and might affect pregnant women differently in different regions of the world. In the international Perinatal Outcomes in the Pandemic (iPOP) Study, we will seize the unique opportunity offered by the COVID-19 pandemic to answer urgent questions about perinatal health. In the first two study phases, we will use population-based aggregate data and standardized outcome definitions to: 1) Determine rates of preterm birth, low birth weight, and stillbirth and describe changes during lockdowns; and assess if these changes are consistent globally, or differ by region and income setting, 2) Determine if the magnitude of changes in adverse perinatal outcomes during lockdown are modified by regional differences in COVID-19 infection rates, lockdown stringency, adherence to lockdown measures, air quality, or other social and economic markers, obtained from publicly available datasets. We will undertake an interrupted time series analysis covering births from January 2015 through July 2020. The iPOP Study will involve at least 121 researchers in 37 countries, including obstetricians, neonatologists, epidemiologists, public health researchers, environmental scientists, and policymakers. We will leverage the most disruptive and widespread natural experiment of our lifetime to make rapid discoveries about preterm birth. Whether the COVID-19 pandemic is worsening or unexpectedly improving perinatal outcomes, our research will provide critical new information to shape prenatal care strategies throughout (and well beyond) the pandemic

Distinct hippocampal engrams control extinction and relapse of fear memory

Learned fear often relapses after extinction, suggesting that extinction training generates a new memory that coexists with the original fear memory; however, the mechanisms governing the expression of competing fear and extinction memories remain unclear. We used activity-dependent neural tagging to investigate representations of fear and extinction memories in the dentate gyrus. We demonstrate that extinction training suppresses reactivation of contextual fear engram cells while activating a second ensemble, a putative extinction engram. Optogenetic inhibition of neurons that were active during extinction training increased fear after extinction training, whereas silencing neurons that were active during fear training reduced spontaneous recovery of fear. Optogenetic stimulation of fear acquisition neurons increased fear, while stimulation of extinction neurons suppressed fear and prevented spontaneous recovery. Our results indicate that the hippocampus generates a fear extinction representation and that interactions between hippocampal fear and extinction representations govern the suppression and relapse of fear after extinction.We thank J. Dunsmoor for comments on the manuscript. A.F.L. was supported by NIH F31 MH111243 and NIH T32 MH106454. S.L.S. was supported by PD/BD/128076/2016 from the Portuguese Foundation for Science and Technology. Research supported by NIH DP5 OD017908 and New York Stem Cell Science (NYSTEM) C-029157 to C.A.D., NIH R01 MH102595 and NIH R21 EY026446 to M.R.

Breastfeeding and the origins of health: Interdisciplinary perspectives and priorities

Breastfeeding and human milk (HM) are critically important to maternal, infant and population health. This paper summarizes the proceedings of a workshop that convened a multidisciplinary panel of researchers to identify key priorities and anticipated breakthroughs in breastfeeding and HM research, discuss perceived barriers and challenges to achieving these breakthroughs and propose a constructive action plan to maximize the impact of future research in this field. Priority research areas identified were as follows: (1) addressing low breastfeeding rates and inequities using mixed methods, community partnerships and implementation science approaches; (2) improving awareness of evidence-based benefits, challenges and complexities of breastfeeding and HM among health practitioners and the public; (3) identifying differential impacts of alternative modes of HM feeding including expressed/pumped milk, donor milk and shared milk; and (4) developing a mechanistic understanding of the health effects of breastfeeding and the contributors to HM composition and variability. Key barriers and challenges included (1) overcoming methodological limitations of epidemiological breastfeeding research and mechanistic HM research; (2) counteracting ‘breastfeeding denialism’ arising from negative personal breastfeeding experiences; (3) distinguishing and aligning research and advocacy efforts; and (4) managing real and perceived conflicts of interest. To advance research on breastfeeding and HM and maximize the reach and impact of this research, larger investments are needed, interdisciplinary collaboration is essential, and the scientific community must engage families and other stakeholders in research planning and knowledge translation

Changes in preterm birth and stillbirth during COVID-19 lockdowns in 26 countries

Funding Information: M.B.A. holds a Tier 2 Canada Research Chair in the Developmental Origins of Chronic Disease at the University of Manitoba and is a Fellow in the Canadian Institutes for Advanced Research (CIFAR) Humans and the Microbiome Program. Her effort on this project was partly supported by HDR UK and ICODA. K.K.C.M. declares support from The Innovation and Technology Commission of the Hong Kong Special Administrative Region Government, and Hong Kong Research Grants Council Collaborative Research Fund Coronavirus Disease (COVID-19) and Novel Infectious Disease Research Exercise (Ref: C7154-20G) and grants from C W Maplethorpe Fellowship, National Institute of Health Research UK, European Commission Framework Horizon 2020 and has consulted for IQVIA Ltd. A.S. is supported by ICODA and HDR UK, and has received a research grant from HDR UK to the BREATHE Hub. He participates on the Scottish and UK Government COVID-19 Advisory Committees, unremunerated. S.J.S. is supported by a Wellcome Trust Clinical Career Development Fellowship (209560/Z/17/Z) and HDR UK, and has received personal fees from Hologic and Natera outside the submitted work. D.B. is supported by a National Health and Medical Research Council (Australia) Investigator Grant (GTN1175744). I.C.K.W. declares support from The Innovation and Technology Commission of the Hong Kong Special Administrative Region Government, and Hong Kong Research Grants Council Collaborative Research Fund Coronavirus Disease (COVID-19) and Novel Infectious Disease Research Exercise (Ref: C7154-20G), and grants from Hong Kong Research Grant Council, National Institute of Health Research UK, and European Commission Framework Horizon 2020. H.Z. is supported by a UNSW Scientia Program Award and reports grants from European Commission Framework Horizon 2020, Icelandic Centre for Research, and Australia’s National Health and Medical Research Council. H.Z. was an employee of the UNSW Centre for Big Data Research in Health, which received funding from AbbVie Australia to conduct research, unrelated to the current study. I.I.A.A., C.D.A., K.A., A.I.A., L.C., S.S., G.E.-G., O.W.G., L. Huicho, S.H., A.K., K.L., V.N., I.P., N.R.R., T.R., T.A.H.R., V.L.S., E.M.S., L.T., R.W. and H.Z. received funding from HDRUK (grant #2020.106) to support data collection for the iPOP study. K.H., R.B., S.O.E., A.R.-P. and J.H. receive salary from ICODA. M.B. received trainee funding from HDRUK (grant #2020.106). J.E.M. received trainee funding from HDRUK (grant #2020.109). Other relevant funding awarded to authors to conduct research for iPOP include: M.G. received funding from THL, Finnish Institute for Health and Welfare to support data collection. K.D. received funding from EDCTP RIA2019 and HDRUK (grant #2020.106) to support data collection. R.B. received funding from Alzheimer’s Disease Data Initiative and ICODA for the development of federated analysis. A.D.M. received funding from HDR UK who receives its funding from the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation (BHF) and the Wellcome Trust; and Administrative Data Research UK, which is funded by the Economic and Social Research Council (grant ES/S007393/1). N.A. received funding from the National Institutes of Health (R35GM138353). O.S received funding from NordForsk (grant #105545). The remaining authors declare no competing interests. Funding Information: Funding and in-kind support: This work was supported by the International COVID-19 Data Alliance (ICODA), an initiative funded by the Bill and Melinda Gates Foundation and Minderoo as part of the COVID-19 Therapeutics Accelerator and convened by Health Data Research (HDR) UK, in addition to support from the HDR UK BREATHE Hub. Several ICODA partners contributed to the study, including: Cytel (statistical support), the Odd Group (data visualization) and Aridhia Informatics (development of federated analysis using a standardized protocol ([Common API] https://github.com/federated-data-sharing/ ) to be used in future work). Additional contributors: We acknowledge the important contributions from the following individuals: A. C. Hennemann and D. Suguitani (patient partners from Prematuridade: Brazilian Parents of Preemies’ Association, Porto Alegre, Brazil); N. Postlethwaite (implementation of processes supporting the trustworthy collection, governance and analysis of data from ICODA, HDR UK, London, UK); A. S. Babatunde (led data acquisition from University of Uyo Teaching Hospital, Uyo, Nigeria); N. Silva (data quality, revision and visualization assessment from Methods, Analytics and Technology for Health (M.A.T.H) Consortium, Belo Horizonte, Brazil); J. Söderling (data management from the Karolinska Institutet, Stockholm, Sweden). We also acknowledge the following individuals who assisted with data collection efforts: R. Goemaes (Study Centre for Perinatal Epidemiology (SPE), Brussels, Belgium); C. Leroy (Le Centre d'Épidémiologie Périnatale (CEpiP), Brussels, Belgium); J. Gamba and K. Ronald (St. Francis Nsambya Hospital, Kampala, Uganda); M. Heidarzadeh (Tabriz Medical University, Tabriz, Iran); M. J. Ojeda (Pontificia Universidad Católica de Chile, Santiago, Chile); S. Nangia (Lady Hardinge Medical College, New Delhi, India); C. Nelson, S. Metcalfe and W. Luo (Maternal Infant Health Section of the Public Health Agency of Canada, Ottawa, Canada); K. Sitcov (Foundation for Health Care Quality, Seattle, United States); A. Valek (Semmelweis University, Budapest, Hungary); M. R. Yanlin Liu (Mater Data and Analytics, Brisbane, Australia). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Funding Information: Funding and in-kind support: This work was supported by the International COVID-19 Data Alliance (ICODA), an initiative funded by the Bill and Melinda Gates Foundation and Minderoo as part of the COVID-19 Therapeutics Accelerator and convened by Health Data Research (HDR) UK, in addition to support from the HDR UK BREATHE Hub. Several ICODA partners contributed to the study, including: Cytel (statistical support), the Odd Group (data visualization) and Aridhia Informatics (development of federated analysis using a standardized protocol ([Common API] https://github.com/federated-data-sharing/) to be used in future work). Additional contributors: We acknowledge the important contributions from the following individuals: A. C. Hennemann and D. Suguitani (patient partners from Prematuridade: Brazilian Parents of Preemies’ Association, Porto Alegre, Brazil); N. Postlethwaite (implementation of processes supporting the trustworthy collection, governance and analysis of data from ICODA, HDR UK, London, UK); A. S. Babatunde (led data acquisition from University of Uyo Teaching Hospital, Uyo, Nigeria); N. Silva (data quality, revision and visualization assessment from Methods, Analytics and Technology for Health (M.A.T.H) Consortium, Belo Horizonte, Brazil); J. Söderling (data management from the Karolinska Institutet, Stockholm, Sweden). We also acknowledge the following individuals who assisted with data collection efforts: R. Goemaes (Study Centre for Perinatal Epidemiology (SPE), Brussels, Belgium); C. Leroy (Le Centre d'Épidémiologie Périnatale (CEpiP), Brussels, Belgium); J. Gamba and K. Ronald (St. Francis Nsambya Hospital, Kampala, Uganda); M. Heidarzadeh (Tabriz Medical University, Tabriz, Iran); M. J. Ojeda (Pontificia Universidad Católica de Chile, Santiago, Chile); S. Nangia (Lady Hardinge Medical College, New Delhi, India); C. Nelson, S. Metcalfe and W. Luo (Maternal Infant Health Section of the Public Health Agency of Canada, Ottawa, Canada); K. Sitcov (Foundation for Health Care Quality, Seattle, United States); A. Valek (Semmelweis University, Budapest, Hungary); M. R. Yanlin Liu (Mater Data and Analytics, Brisbane, Australia). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Publisher Copyright: © 2023, The Author(s).Preterm birth (PTB) is the leading cause of infant mortality worldwide. Changes in PTB rates, ranging from −90% to +30%, were reported in many countries following early COVID-19 pandemic response measures (‘lockdowns’). It is unclear whether this variation reflects real differences in lockdown impacts, or perhaps differences in stillbirth rates and/or study designs. Here we present interrupted time series and meta-analyses using harmonized data from 52 million births in 26 countries, 18 of which had representative population-based data, with overall PTB rates ranging from 6% to 12% and stillbirth ranging from 2.5 to 10.5 per 1,000 births. We show small reductions in PTB in the first (odds ratio 0.96, 95% confidence interval 0.95–0.98, P value <0.0001), second (0.96, 0.92–0.99, 0.03) and third (0.97, 0.94–1.00, 0.09) months of lockdown, but not in the fourth month of lockdown (0.99, 0.96–1.01, 0.34), although there were some between-country differences after the first month. For high-income countries in this study, we did not observe an association between lockdown and stillbirths in the second (1.00, 0.88–1.14, 0.98), third (0.99, 0.88–1.12, 0.89) and fourth (1.01, 0.87–1.18, 0.86) months of lockdown, although we have imprecise estimates due to stillbirths being a relatively rare event. We did, however, find evidence of increased risk of stillbirth in the first month of lockdown in high-income countries (1.14, 1.02–1.29, 0.02) and, in Brazil, we found evidence for an association between lockdown and stillbirth in the second (1.09, 1.03–1.15, 0.002), third (1.10, 1.03–1.17, 0.003) and fourth (1.12, 1.05–1.19, <0.001) months of lockdown. With an estimated 14.8 million PTB annually worldwide, the modest reductions observed during early pandemic lockdowns translate into large numbers of PTB averted globally and warrant further research into causal pathways.Peer reviewe

Changes in preterm birth and stillbirth during COVID-19 lockdowns in 26 countries.

Preterm birth (PTB) is the leading cause of infant mortality worldwide. Changes in PTB rates, ranging from -90% to +30%, were reported in many countries following early COVID-19 pandemic response measures ('lockdowns'). It is unclear whether this variation reflects real differences in lockdown impacts, or perhaps differences in stillbirth rates and/or study designs. Here we present interrupted time series and meta-analyses using harmonized data from 52 million births in 26 countries, 18 of which had representative population-based data, with overall PTB rates ranging from 6% to 12% and stillbirth ranging from 2.5 to 10.5 per 1,000 births. We show small reductions in PTB in the first (odds ratio 0.96, 95% confidence interval 0.95-0.98, P value <0.0001), second (0.96, 0.92-0.99, 0.03) and third (0.97, 0.94-1.00, 0.09) months of lockdown, but not in the fourth month of lockdown (0.99, 0.96-1.01, 0.34), although there were some between-country differences after the first month. For high-income countries in this study, we did not observe an association between lockdown and stillbirths in the second (1.00, 0.88-1.14, 0.98), third (0.99, 0.88-1.12, 0.89) and fourth (1.01, 0.87-1.18, 0.86) months of lockdown, although we have imprecise estimates due to stillbirths being a relatively rare event. We did, however, find evidence of increased risk of stillbirth in the first month of lockdown in high-income countries (1.14, 1.02-1.29, 0.02) and, in Brazil, we found evidence for an association between lockdown and stillbirth in the second (1.09, 1.03-1.15, 0.002), third (1.10, 1.03-1.17, 0.003) and fourth (1.12, 1.05-1.19, <0.001) months of lockdown. With an estimated 14.8 million PTB annually worldwide, the modest reductions observed during early pandemic lockdowns translate into large numbers of PTB averted globally and warrant further research into causal pathways

Changes in preterm birth and stillbirth during COVID-19 lockdowns in 26 countries.

Preterm birth (PTB) is the leading cause of infant mortality worldwide. Changes in PTB rates, ranging from -90% to +30%, were reported in many countries following early COVID-19 pandemic response measures ('lockdowns'). It is unclear whether this variation reflects real differences in lockdown impacts, or perhaps differences in stillbirth rates and/or study designs. Here we present interrupted time series and meta-analyses using harmonized data from 52 million births in 26 countries, 18 of which had representative population-based data, with overall PTB rates ranging from 6% to 12% and stillbirth ranging from 2.5 to 10.5 per 1,000 births. We show small reductions in PTB in the first (odds ratio 0.96, 95% confidence interval 0.95-0.98, P value <0.0001), second (0.96, 0.92-0.99, 0.03) and third (0.97, 0.94-1.00, 0.09) months of lockdown, but not in the fourth month of lockdown (0.99, 0.96-1.01, 0.34), although there were some between-country differences after the first month. For high-income countries in this study, we did not observe an association between lockdown and stillbirths in the second (1.00, 0.88-1.14, 0.98), third (0.99, 0.88-1.12, 0.89) and fourth (1.01, 0.87-1.18, 0.86) months of lockdown, although we have imprecise estimates due to stillbirths being a relatively rare event. We did, however, find evidence of increased risk of stillbirth in the first month of lockdown in high-income countries (1.14, 1.02-1.29, 0.02) and, in Brazil, we found evidence for an association between lockdown and stillbirth in the second (1.09, 1.03-1.15, 0.002), third (1.10, 1.03-1.17, 0.003) and fourth (1.12, 1.05-1.19, <0.001) months of lockdown. With an estimated 14.8 million PTB annually worldwide, the modest reductions observed during early pandemic lockdowns translate into large numbers of PTB averted globally and warrant further research into causal pathways